from transformers import AutoTokenizer, AutoModel, AutoConfig
import torch.nn as nn

'''
BERT+BiLSTM+CRF 结构为demo
'''
class AssembleModel(nn.Module):
    def __init__(self, config):
        super(AssembleModel, self).__init__()
        pass

    def freeze(self, _layer):  # 冻结某些网络的参数(即不参与反向传播)
        for p in _layer.parameters():
            p.requires_grad = False
        return _layer

    def _get_feature(self, src, mask):
        return 

    def forward(self):
        emissions = self._get_feature()
        return
    